Long-read genome sequencing identifies causal structural variation in a Mendelian disease.

PurposeCurrent clinical genomics assays primarily utilize short-read sequencing (SRS), but SRS has limited ability to evaluate repetitive regions and structural variants. Long-read sequencing (LRS) has complementary strengths, and we aimed to determine whether LRS could offer a means to identify overlooked genetic variation in patients undiagnosed by SRS.MethodsWe performed low-coverage genome LRS to identify structural variants in a patient who presented with multiple neoplasia and cardiac myxomata, in whom the results of targeted clinical testing and genome SRS were negative.ResultsThis LRS approach yielded 6,971 deletions and 6,821 insertions > 50 bp. Filtering for variants that are absent in an unrelated control and overlap a disease gene coding exon identified three deletions and three insertions. One of these, a heterozygous 2,184 bp deletion, overlaps the first coding exon of PRKAR1A, which is implicated in autosomal dominant Carney complex. RNA sequencing demonstrated decreased PRKAR1A expression. The deletion was classified as pathogenic based on guidelines for interpretation of sequence variants.ConclusionThis first successful application of genome LRS to identify a pathogenic variant in a patient suggests that LRS has significant potential for the identification of disease-causing structural variation. Larger studies will ultimately be required to evaluate the potential clinical utility of LRS.

RNA-Seq mapping and detection of gene fusions with a suffix array algorithm.

High-throughput RNA sequencing enables quantification of transcripts (both known and novel), exon/exon junctions and fusions of exons from different genes. Discovery of gene fusions-particularly those expressed with low abundance- is a challenge with short- and medium-length sequencing reads. To address this challenge, we implemented an RNA-Seq mapping pipeline within the LifeScope software. We introduced new features including filter and junction mapping, annotation-aided pairing rescue and accurate mapping quality values. We combined this pipeline with a Suffix Array Spliced Read (SASR) aligner to detect chimeric transcripts. Performing paired-end RNA-Seq of the breast cancer cell line MCF-7 using the SOLiD system, we called 40 gene fusions among over 120,000 splicing junctions. We validated 36 of these 40 fusions with TaqMan assays, of which 25 were expressed in MCF-7 but not the Human Brain Reference. An intra-chromosomal gene fusion involving the estrogen receptor alpha gene ESR1, and another involving the RPS6KB1 (Ribosomal protein S6 kinase beta-1) were recurrently expressed in a number of breast tumor cell lines and a clinical tumor sample.

Analysis of Cooperativity and Group Additivity in the Hydration of 1,2-Dimethoxyethane.

We calculate hydration free energies of 1,2-dimethoxyethane (DME) conformations in water at 298 K and 1 bar. We find that the preference for the two most abundant tgt and tgg conformations derives from favorable nonspecific (i.e., long-range) solute-water interactions that are partially offset by unfavorable free energies of forming cavities in water to accommodate these conformations. The much lower population of the third most abundant tg+g- conformation, the most abundant conformation in the ideal gas at 298 K, is attributed to less favorable long-range solute-water interactions. We also find that long-range methyl/methylene group-water and ether oxygen-water interactions make significant nonadditive contributions to the free energy of DME hydration and propose a method based on quasichemical theory for reducing these nonadditive contributions by identifying constituent groups of DME that minimize the covariance in the long-range methyl/methylene group-water and ether oxygen-water interactions. We apply this method to show that the decomposition of DME into its constituent dimethyl ether groups is a better approximation of group additivity than decompositions based on distinguishing hydrophobic/hydrophilic constituent groups.